Data Engineer I: ETL & Big Data on GCP

Bzpp; United States; On-site; USD 110,000 - 150,000; Full time

Job summary

Bzpp is seeking a data engineer to design and develop scalable ETL pipelines on cloud platforms, ingesting data from databases, APIs, and files. The role emphasizes SQL transformations on BigQuery, production support, and data quality reporting.

The candidate will contribute to data modeling, analytics, and security while following engineering best practices and tooling like GitHub, Jira, and Confluence.

Qualifications

• Bachelor’s degree in Computer Science, Applied Computer Science, Computer Applications, Computer Engineering, Information Technology, a related field, or a foreign equivalent plus 3 years post-baccalaureate experience in job offered or any engineering/IT related job titles.

Responsibilities

• Document scope and requirements through interactions with analysts and stakeholders.
• Design and develop scalable ETL pipelines on Cloud platforms using big data technologies.
• Ingest data from Relational databases, APIs, and files.
• Develop complex SQL transformations on BigQuery.
• Provide production support, job scheduling/monitoring, ETL data quality reporting.
• Contribute to software development and data modeling for business decision-making.
• Establish software and infrastructure to analyze big data and ensure data integrity and security.

Skills

Python analytics

ETL with Python/SQL

GitHub & VS Code

SQL data manipulation

AB/multivariate tests

GCP BigQuery/Kubernetes/Composer

Data viz dashboards

Jira & Confluence

Big data production support

Education

Bachelor’s degree in CS or related field with 3 years experience

Tools

Apache Airflow

Job description

Bzpp is seeking a data engineer to design and develop scalable ETL pipelines on cloud platforms, ingesting data from databases, APIs, and files. The role emphasizes SQL transformations on BigQuery, production support, and data quality reporting.

The candidate will contribute to data modeling, analytics, and security while following engineering best practices and tooling like GitHub, Jira, and Confluence.